Abstract
This article discusses the possibility of building in real-time a mosaic of the seafloor relying on a simultaneous localization and mapping (SLAM) framework. The goal is to provide an unmanned underwater vehicle with a relatively rough visual map of the seafloor to support basic navigation and context awareness. To achieve that goal, an accurate estimation of the location of the visual landmarks and, in particular, the correct data association when a visual landmark is re-visited by the vehicle are the crucial points. Instead of using a global mosaic, this work uses the combination of a set of local mosaics constructed in the vicinity of the SLAM visual landmarks. The contributions of this article are mainly the use of SURF features, the local mosaics approach and the real-time capability. The use of SURF features allows eliminating false positives in the data association of SLAM visual landmarks. The local mosaics approach is an effective way of correcting the effects of the drift on the mosaic in real time. The main contribution is the real-time capability as it will be seen. The algorithm was tested using a batch of experimental data in typical operating conditions and the results prove the effectiveness of the approach.
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Bailey T, Durrant-Whyte H (2006) Simultaneous localization and mapping (slam): part ii. Robotics Autom Mag IEEE 13(3): 108–117. doi:10.1109/MRA.2006.1678144
Bay H, Tuytelaars T, Gool LV (2006) Surf: speeded up robust features. In: Proceedings of the 9th European conference on computer vision, part 1, vol 3951. Springer LNCS, Berlin, pp 404–417
Bosse M, Newman P, Leonard J, Teller S (2004) Simultaneous localization and map building in large-scale cyclic environments using the atlas framework. Int J Robotics Res 23(12): 1113–1139
Caccia M (2006) Vision-based SLAM for ROVs: preliminary experimental results. In: Proc. of 7th IFAC conference on manoeuvring and control of marine craft, Lisbon, Portugal
Caccia M (2007) Vision-based ROV horizontal motion control: near-seafloor experimental results. Control Eng Pract 15(6): 703–714
Caccia M, Bruzzone G, Ferreira F, Veruggio G (2009) Online video mosaicking through slam for rovs. In: OCEANS 2009-EUROPE, 2009. OCEANS ’09, pp 1–6. doi:10.1109/OCEANSE.2009.5278217
Cornelis N, Van Gool L (2008) Fast scale invariant feature detection and matching on programmable graphics hardware. In: Computer vision and pattern recognition workshops, 2008. CVPRW ’08. IEEE Computer Society Conference, pp 1–8. doi:10.1109/CVPRW.2008.4563087
Dissanayake M, Newman P, Clark S, Durrant-Whyte H, Csorba M (2001) A solution to the simultaneous localization and map building (SLAM) problem. IEEE Transact Robotics Autom 17(3): 229–241
Durrant-Whyte H, Bailey T (2006) Simultaneous localization and mapping: part i. Robotics Autom Mag IEEE 13(2): 99–110. doi:10.1109/MRA.2006.1638022
Eustice R, Pizarro O, Singh H, Ma WH (2004) Visually augmented navigation in an unstructured environment using a delayed state history. In: Proc. IEEE int. conf. on robotics and automation, pp 25–32
Eustice R, Pizarro O, Singh H (2008) Visually augmented navigation for autonomous underwater vehicles. IEEE J Ocean Eng 33(2): 103–122
Fairfield N, Kantor G, Wettergreen D (2005) Three dimensional evidence grids for SLAM in complex underwater environments. In: Proc. of 14th international symposium of unmanned untethered submersible technology (UUST), AUSI, New Hampshire
Fairfield N, Kantor GA, Jonak D, Wettergreen D (2010) Segmented slam in three-dimensional environments. J Field Robotics 27(1): 85–103
Ferreira F, Veruggio G, Caccia M, Bruzzone G (2009) Speeded up robust features for vision-based underwater motion estimation and slam: comparison with correlation-based techniques. In: Proceedings of MCMC’2009
Ferreira F, Orsenigo F, Veruggio G, Pavlakis P, Caccia M, Bruzzone G (2010) Comparison between feature-based and phase correlation methods for ROV vision-based speed estimation. In: 7th symposium on intelligent autonomous vehicles. IFAC, Lecce
Fischler MA, Bolles RC (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun ACM 24: 381–395. doi:10.1145/358669.358692
Garcia R, Puig J, Ridao P, Cufi X (2002) Augmented state kalman filtering for auv navigation. In: Robotics and automation, 2002. Proceedings. ICRA ’02. IEEE international conference, vol 4, pp 4010–4015. doi:10.1109/ROBOT.2002.1014362
Garcia R, Cufi X, Carreras M, Ridao P (2003a) Correction of shading effects in vision-based uuv localization. In: Robotics and automation, 2003. Proceedings. ICRA ’03. IEEE international conference, vol 1, pp 989–994. doi:10.1109/ROBOT.2003.1241721
Garcia R, Nicosevici T, Ridao P, Ribas D (2003b) Towards a real-time vision-based navigation system for a small-class uuv. In: Intelligent robots and systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ international conference, vol 1, pp 818–823. doi:10.1109/IROS.2003.1250730
Gracias N, Van der Zwaan S, Bernardino A, Santos-Victor J (2003) Mosaic-based navigation for autonomous underwater vehicles. IEEE J Ocean Eng 28(4): 609–624
Johnson-Roberson M, Pizarro O, Williams SB, Mahon I (2010) Generation and visualization of large-scale three-dimensional reconstructions from underwater robotic surveys. J Field Robot 27(1): 21–51. doi:10.1002/rob.v27:1
Kudzinava M (2007) Feature-based matching of underwater images. Master’s thesis, University of Girona
Leonard J, Durrant-Whyte H (1991) Simultaneous map building and localization for an autonomous mobile robot. In: Intelligent robots and systems ’91. ’Intelligence for Mechanical Systems, Proceedings IROS ’91. IEEE/RSJ international workshop. vol 3, pp 1442–1447. doi:10.1109/IROS.1991.174711
Leonard J, Feder H (2001) Decoupled stochastic mapping. IEEE J Ocean Eng 26(4): 561–571
Lina María Paz JDT, Neira J (2008) Divide and conquer: Ekf slam in o(n). IEEE Transact Robotics 24(5): 1107–1120
Lisien B, Morales D, Silver D, Kantor GA, Rekleitis I, Choset H (2005) The hierarchical atlas. IEEE Transact Robotics 21(1): 473–481
Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2): 91–110
Marks R, Rock S, Lee M (1995) Real-time video mosaicking of the ocean floor. IEEE J Ocean Eng 20(3): 229–241
Misu T, Hashimoto T, Ninomiya K (1999) Optical guidance for autonomous landing of spacecraft. IEEE Transact Aerospace Electron Syst 35(2): 459–473
Mozos OM, Gil A, Ballesta M, Reinoso O (2007) Interest point detectors for visual slam. Tech. rep., LNAI 4788, pp 170–179
Negahdaripour S, Xu X (2002) Mosaic-based positioning and improved motion-estimation methods for automatic navigation of submersible vehicles. IEEE J Ocean Eng 27(1): 79–99
Piniés P, Tardós JD (2008) Large scale slam building conditionally independent local maps: Application to monocular vision. IEEE Transact Robotics 24(5): 1094–1106
Pizarro O, Eustice R, Singh H (2009) Large area 3-d reconstructions from underwater optical surveys. IEEE J Ocean Eng 34(2): 150–169
Ribas D, Ridao P, Tardós JD, Neira J (2008) Underwater slam in man-made structured environments. J Field Robotics 25(11–12): 898–921. doi:10.1002/rob.v25:11/12
Richmond K (2009) Real-time visual mosaicking and navigation on the seafloor. PhD thesis, Stanford University
Richmond K, Rock S (2005) A real-time visual mosaicking and navigation system. In: Proceedings of the unmanned untethered submersible technology conference (UUST), Durham
Richmond K, Rock S (2007a) An operational real-time large-scale visual mosaicking and navigation system. Sea Technol 48:10–13
Richmond K, Rock S (2007b) Real-time visual mosaicking and navigation of the uss macon. In: Proceedings of the unmanned untethered submersible technology conference (UUST), Durham
Roman CN, Singh H (2007) A self-consistent bathymetric mapping algorithm. J Field Robotics 24(1–2): 23–50
Ruiz I, de Raucourt S, Petillot Y, Lane D (2004) Concurrent mapping and localization using sidescan sonar. IEEE J Ocean Eng 29(2): 442–456
Sinha S, Frahm JM, Pollefeys M, Genc Y (2007) Feature tracking and matching in video using programmable graphics hardware. Mach Vis Appl. doi:10.1007/s00138-007-0105-z
Smith RC, Cheeseman P (1987) On the representation and estimation of spatial uncertainly. Int J Robotics Res 5(4): 56–68. doi:10.1177/027836498600500404
Thomas SJ (2008) Real-time stereo visual slam. Master’s thesis, Heriot-Watt University, Universitat de Girona, Universite de Bourgogne
Thrun S, Fox D, Burgard W (1998) A probabilistic approach to concurrent mapping and localization for mobile robots. Mach Learn 31:29–53; also appeared in Autonom Robots 5:253–271 (joint issue)
Thrun S, Burgard W, Fox D (2005) Probablistic robotics. Intelligent robotics and autonomous agents. The MIT Press, Cambridge
Vincent A, Pessel N, Borgetto M, Jouffroy J, Opderbecke J, Rigaud V (2003) Real-time geo-referenced video mosaicking with the matisse system. In: OCEANS 2003. Proceedings, vol 4, pp 2319–2324. doi:10.1109/OCEANS.2003.178271
Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Computer vision and pattern recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE computer society conference, vol 1, pp I-511–I-518. doi:10.1109/CVPR.2001.990517
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Ferreira, F., Veruggio, G., Caccia, M. et al. Real-time optical SLAM-based mosaicking for unmanned underwater vehicles. Intel Serv Robotics 5, 55–71 (2012). https://doi.org/10.1007/s11370-011-0103-x
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DOI: https://doi.org/10.1007/s11370-011-0103-x